Patient Perception and Trust in Artificial Intelligence in Dental Care: A Systematic Review

Background: Patient trust may determine whether artificial intelligence (AI) is accepted in dental care, particularly when AI contributes to diagnosis or treatment planning. We aimed to synthesize patient-reported trust, confidence, acceptance, and preferences regarding dental AI and to identify factors associated with these outcomes. Methods: PubMed/MEDLINE, Scopus, and Web of Science were searched from database inception to 2 June 2026. Two reviewers independently screened records and extracted data. Risk of bias was assessed with the revised JBI tool for analytical cross-sectional studies. Because outcomes and metrics were heterogeneous, findings were synthesized narratively. The review was registered in PROSPERO (CRD420261439049). Results: The final synthesis included eight studies comprising 3171 participants from five countries. Attitudes were generally favourable when AI supported rather than replaced dentists. In one study, 47.7% accepted AI-assisted interpretation of diagnostic data, whereas 10.8% trusted an entirely AI-generated diagnosis. Another study found that 84.9% supported AI analysis of dental images followed by dentist review. A fixed-order vignette study improved lesion recognition but did not significantly change trust in the dentist. Interpretation was limited by non-probability sampling, heterogeneous and often non-validated measures, incomplete control of confounding, and reporting inconsistencies. Conclusions: Available evidence suggests conditional acceptance of dental AI, particularly when dentists retain oversight. Confidence in the prevalence estimates of trust and acceptance is low; these findings do not establish that AI improves trust. More representative studies using validated, conceptually distinct outcome measures are required.